New, Virtually Wall-Less Cannulas Designed for Augmented Venous Drainage in Minimally Invasive Cardiac Surgery
Bibliographic record
Abstract
OBJECTIVE: Inadequate venous drainage during minimally invasive cardiac surgery becomes most evident when the blood trapped in the pulmonary circulation floods the surgical field. The present study was designed to assess the in vivo performance of new, thinner, virtually wall-less, venous cannulas designed for augmented venous drainage in comparison to traditional thin-wall cannulas. METHODS: Remote cannulation was realized in 5 bovine experiments (74.0 ± 2.4 kg) with percutaneous venous access over the wire, serial dilation up to 18 F and insertion of either traditional 19 F thin wall, wire-wound cannulas, or through the same access channel, new, thinner, virtually wall-less, braided cannulas designed for augmented venous drainage. A standard minimal extracorporeal circuit set with a centrifugal pump and a hollow fiber membrane oxygenator, but no in-line reservoir was used. One hundred fifty pairs of pump-flow and required pump inlet pressure values were recorded with calibrated pressure transducers and a flowmeter calibrated by a volumetric tank and timer at increasing pump speed from 1500 RPM to 3500 RPM (500-RPM increments). RESULTS: Pump flow accounted for 1.73 ± 0.85 l/min for wall-less versus 1.17 ± 0.45 l/min for thin wall at 1500 RPM, 3.91 ± 0.86 versus 3.23 ± 0.66 at 2500 RPM, 5.82 ± 1.05 versus 4.96 ± 0.81 at 3500 RPM. Pump inlet pressure accounted for 9.6 ± 9.7 mm Hg versus 4.2 ± 18.8 mm Hg for 1500 RPM, -42.4 ± 26.7 versus -123 ± 51.1 at 2500 RPM, and -126.7 ± 55.3 versus -313 ± 116.7 for 3500 RPM. CONCLUSIONS: At the well-accepted pump inlet pressure of -80 mm Hg, the new, thinner, virtually wall-less, braided cannulas provide unmatched venous drainage in vivo. Early clinical analyses have confirmed these findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".